Updates
Model and report changes
- The model has the ability to incorporate estimates of community prevalence, by region and age group, from the Office of National Statistics COVID-19 Infection Survey (see Data Sources for details). These are included weekly over the last 8 weeks and for the age groups >4 years to inform trends in incidence that are too recent to be captured by the data on deaths. In recent weeks we have been using these data, but do not include them in the analysis here due to the difficulty in resolving conflicting signals coming from the two datasets.
- The model now accounts for the ongoing immunisation programme, stratifying the population of people still susceptible to infection with the virus according to their immunisation status (unimmunised/1 dose/2 doses). We use data on the daily proportions of the population getting immunised to inform this splitting of the population, assuming that it takes three weeks for vaccine-derived immunity to develop .
- The geographical definition has been changed from the seven NHS regions (map) to the nine regions typically used in government (map). This new spatial definition more appropriately reflects the existing regional heterogeneity.
- Using observations of improved survival in hospitalised COVID-19 patients, we have allowed the probability of dying following infection with SARS-CoV2 (the infection-fatality rate, IFR) to gradually change over the course of June 2020, with a decrease being estimated. More recently, the Kent variant of the virus has gradually become the predominant virus strain and we accordingly allow for a change in the IFR over the period in which the relative prevalence of this strain has been growing.
- The ‘Epidemic summary’ now only reports the current value for the IFR by age. To visualise how this has changed over time in our model, see the IFR tab in the ‘Infections and Deaths’ section of the report. The quantity that is now plotted under this tab is the probability of dying if infected, taking into account the impact of the immunisation programme.
- The modelling now accounts for a different susceptibility to infection in the under-15s, using information from literature (Viner et al, 2020) suggesting that children less likely to acquire infection when in contact with an infectious individual.
Updated findings
- The current estimate of the daily number of new infections occurring each day across England is 12,900 (5,890–27,500, 95% credible interval).
- The daily infection rate is highest in the East Midlands (EM), North West (NW) and West Midlands (WM) with 1,910, 2,540 and 1,680 new daily infections, corresponding to 40, 35 and 28 per 100,000 population, respectively. Note that a substantial proportion of these daily infections will be asymptomatic.
- We predict that the number of deaths occurring daily is likely to remain low with a forecast for the period around the 16th April suggesting that there will be fewer than 175 deaths per day and potentially as few as 35 deaths per day.
- The probability of Rt exceeding 1 is 64%, 63% and 62% in the NW, EM and WM, respectively; 41% in the in the East of England (EE) and North East (NE); around 30% in Yorkshire and Humber (YH) and South East (SE); and approximately 15% in London and South West (SW).
- The growth rate for England is estimated to be positive at 0.02 (-0.02–0.05, 95% credible interval) per day. This means that, nationally, the number of infections is increasing, although there is heterogeneity across regions, with negative growth in some regions.
- London, followed by the WM, NW and EE, continues to have the highest attack rate, that is the proportion of the population who have ever been infected, with 38%, 31% and 25% respectively. The SW continues to have the lowest attack rate at 10%.
- Note that the deaths data used are only very weakly informative on Rt over the last two weeks. Therefore, the estimate for current incidence, Rt and the forecast of daily numbers of deaths are likely to be subject to some revision.
Interpretation
The plots of the estimated Rt over time are showing an increase, following a period of downwards trends from the introduction of the national lockdown in January. The Rt for some regions are around 1 (EM, NW, WM), although these estimates are quite uncertain and the upper bounds include values much higher than 1. This anticipated increase in the Rt is mostly driven by the school reopening from March 8th, the impact of which will not yet have filtered through to the data on deaths.
The incidence of deaths has continued to fall sharply in all regions and it is predicted to plateau at low values, with some initial evidence of a resurgence in the northern regions. This pattern is also shared by the estimated number of new infections, with a potential increase in the Midlands and northern regions.
The plot of the infection fatality rate (IFR) shows an increasing mortality risk from September onwards (at least in the over-45s) until the immunisation programme begins to show an impact. At the end of January we estimate a decreasing IFR in all adult age groups, but most steeply at older ages. The overall IFR falls to about 6-7% in the over-75s and 0.3% overall.
Other indicators (e.g. hospital bed prevalence, reported new cases) continue to suggest a declining epidemic. Prevalence of disease is now around 0.25% in England with high regional heterogeneity. Some evidence for a resurgence in transmission is evident in the ONS Community Infections Survey, where prevalence is increasing in secondary school age children and in the North East and Yorkshire in particular.
Summary
Real-time tracking of an epidemic, as data accumulate over time, is an essential component of a public health response to a new outbreak. A team of statistical modellers at the MRC Biostatistics Unit (BSU), University of Cambridge, are working to provide regular now-casts and forecasts of COVID-19 infections and deaths. This information feeds directly to the SAGE sub-group, Scientific Pandemic Influenza sub-group on Modelling (SPI-M), and to regional Public Health England (PHE) teams.
Methods
We fit a transmission model (Birrell et al. 2020) to a number of data sources (see ‘Data Sources’), to reconstruct the number of new COVID-19 infections over time in different age groups and NHS regions, estimate a measure of ongoing transmission and predict the number of new COVID-19 deaths.
Data sources
We use:
- Data on COVID-19 confirmed deaths from the Public Health England (PHE) line-listing This consists of a combination of deaths notified to:
- the Demographics Batch Service (DBS), a mechanism that allows PHE to submit a file of patient information to the National Health Service spine for tracing against the personal demographics service (PDS). PHE submit a line list of patients diagnosed with COVID-19 to DBS daily. The file is returned with a death flag and date of death updated (started 20th March, 2020).
- NHS England, who report data from NHS trusts relating to patients who have died after admission to hospital or within emergency department settings.
- Health Protection Teams (HPTs), resulting from a select survey created by PHE to capture deaths occurring outside of hospital settings, e.g. care homes (started 23rd March, 2020)
- Data on antibody prevalence in blood samples from a PHE survey of NHS Blood Transfusion (NHSBT) donors.
Data are stratified into eight age groups: <1, 1-4, 5-14, 15-24, 25-44, 45-64, 65-74, 75+, and the NHS England regions (North East and Yorkshire, North West, Midlands, East of England, London, South East, South West).
- Published information on the the natural history of COVID-19 (Verity et al., 2020; Li et al, 2020)
- Information on contacts between different age groups from:
- A Survey that describes relative rates of contacts between different age groups (Mossong et al. 2008).
- Google Community Mobility reports, informing the changes in people’s mobility over the course of the pandemic, particularly after the March 23rd lockdown measures.
- The ONS’ time use survey, which in conjunction with the google mobility study, allows estimation of the changing exposure to infection risk over time.
- Data from the Department for Education describing the proportion of children currently attending school.
- Daily data on the numbers of people getting immunised by age-group and region. These data are derived from the National Immunisation Management Service (NIMS). These data includes all COVID-19 immunisations administered at hospital hubs, local immunisation service sites such as GP practices, and dedicated immunisation centres.
Epidemic summary
Current \(R_t\)
Value of \(R_t\), the average number of secondary infections due to a typical infection today.
Attack rate
The percentage of a given group that has been infected.
Change in infections incidence
Growth rates
NB: negative growth rates are rates of decline. Values are daily changes.
| England |
0.02 |
-0.02 |
0.05 |
| East of England |
-0.02 |
-0.10 |
0.06 |
| East Midlands |
0.01 |
-0.06 |
0.07 |
| London |
-0.04 |
-0.12 |
0.03 |
| North East |
-0.01 |
-0.09 |
0.06 |
| North West |
0.01 |
-0.06 |
0.07 |
| South East |
-0.02 |
-0.09 |
0.04 |
| South West |
-0.04 |
-0.13 |
0.04 |
| West Midlands |
0.01 |
-0.08 |
0.07 |
| Yorkshire and The Humber |
-0.02 |
-0.09 |
0.04 |
Halving times
Halving times in days, if a region shows growth than value will be NA.
| England |
NA |
44.88 |
NA |
| East of England |
39.86 |
6.84 |
NA |
| East Midlands |
NA |
10.96 |
NA |
| London |
16.76 |
5.49 |
NA |
| North East |
59.59 |
7.28 |
NA |
| North West |
NA |
10.78 |
NA |
| South East |
33.16 |
6.99 |
NA |
| South West |
15.34 |
4.87 |
NA |
| West Midlands |
NA |
8.33 |
NA |
| Yorkshire and The Humber |
43.48 |
7.34 |
NA |
Doubling times
Doubling times in days, if a region shows decline then the value will be NA.
| England |
41.52 |
12.99 |
NA |
| East of England |
NA |
12.12 |
NA |
| East Midlands |
89.52 |
10.44 |
NA |
| London |
NA |
21.84 |
NA |
| North East |
NA |
11.80 |
NA |
| North West |
81.80 |
10.28 |
NA |
| South East |
NA |
17.20 |
NA |
| South West |
NA |
18.11 |
NA |
| West Midlands |
130.80 |
10.06 |
NA |
| Yorkshire and The Humber |
NA |
15.66 |
NA |
Change in deaths incidence
Growth rates
NB: negative growth rates are rates of decline. Values are daily changes.
| England |
-0.04 |
-0.05 |
-0.01 |
| East of England |
-0.06 |
-0.08 |
-0.01 |
| East Midlands |
-0.03 |
-0.06 |
0.03 |
| London |
-0.06 |
-0.08 |
-0.02 |
| North East |
-0.04 |
-0.07 |
0.02 |
| North West |
-0.03 |
-0.06 |
0.03 |
| South East |
-0.05 |
-0.07 |
0.00 |
| South West |
-0.07 |
-0.09 |
-0.02 |
| West Midlands |
-0.04 |
-0.07 |
0.02 |
| Yorkshire and The Humber |
-0.04 |
-0.07 |
0.01 |
Halving times
Halving times in days, if a region shows growth than value will be NA.
| England |
19.34 |
13.03 |
52.96 |
| East of England |
10.72 |
7.86 |
47.34 |
| East Midlands |
25.89 |
10.74 |
NA |
| London |
10.62 |
7.91 |
34.58 |
| North East |
17.52 |
9.17 |
NA |
| North West |
24.78 |
10.43 |
NA |
| South East |
14.49 |
9.10 |
286.72 |
| South West |
9.92 |
7.38 |
43.95 |
| West Midlands |
17.05 |
8.95 |
NA |
| Yorkshire and The Humber |
15.72 |
9.29 |
NA |
Doubling times
Doubling times in days, if a region shows decline then the value will be NA.
| England |
NA |
NA |
NA |
| East of England |
NA |
NA |
NA |
| East Midlands |
NA |
24.45 |
NA |
| London |
NA |
NA |
NA |
| North East |
NA |
30.32 |
NA |
| North West |
NA |
24.20 |
NA |
| South East |
NA |
NA |
NA |
| South West |
NA |
NA |
NA |
| West Midlands |
NA |
34.46 |
NA |
| Yorkshire and The Humber |
NA |
137.20 |
NA |
Infections and deaths
The shaded areas show periods of national lockdown, the green lines the dates (once confirmed) of the steps in the roadmap in the UK Governement’s COVID-19 Response – Spring 2021, and the red line shows the date these results were produced (26 Mar).
Prob \(R_t > 1\)
The figure below shows the probability that \(R_t\) is greater than 1 (ie: the number of infections is growing) in each region over time. Clicking the regions in the legend allows lines to be added or removed from the figure.
Copyright © MRC Biostatistics Unit, University of Cambridge